Indian Journal of Pharmacy & Drug Studies
Discipline: Pharmaceutical Sciences ISSN: XXXX-XXXX Starting Year: 2022 Current volume: Volume 5 Issue per year: 4 issues Indexing: Google Scholar Editor-in-chief: Kumaraswamy Gandla E-mail: editor.ijpds@mansapublishers.com
Spinal Muscular Atrophy in the Era of Precision Medicine: Pathophysiology, Therapeutic Advances, and Future Perspectives
Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder caused by biallelic loss-of-function mutations in the survival motor neuron 1 (SMN1) gene, resulting in progressive degeneration of anterior horn cells and consequent proximal muscle weakness. Historically one of the leading monogenic causes of infant mortality, SMA has undergone a paradigm shift in its clinical outlook over the past decade, driven by the development and regulatory approval of three disease-modifying therapies: nusinersen, an antisense oligonucleotide targeting SMN2 pre-mRNA splicing; onasemnogene abeparvovec, an adeno-associated virus serotype 9 (AAV9)-mediated gene replacement therapy; and risdiplam, an orally bioavailable small-molecule SMN2 splicing modifier. These advances have transformed SMA from a uniformly fatal or severely debilitating condition into one amenable to substantial clinical stabilization and, in presymptomatic cases, near-normal neurodevelopmental trajectories. This review provides a comprehensive synthesis of the current understanding of SMA, encompassing its molecular genetics, pathophysiological mechanisms, clinical classification, diagnostic approaches, and the evolving therapeutic landscape. Particular emphasis is placed on recently approved and investigational agents, the role of newborn screening in enabling presymptomatic intervention, and outstanding challenges including treatment access, long-term efficacy, combinatorial strategies, and the management of non-responders. By integrating recent evidence from high-impact clinical trials and translational studies, this review aims to serve as an authoritative reference for clinicians and researchers engaged in the care and study of SMA.
Copyright (c) 2026 Rukmangathan Palani, Senthilnathan D N, Praveena S, Abishek T https://creativecommons.org/licenses/by-nc-nd/4.0
Antibacterial and Antifungal Activities of Water Hyacinth (Eichhornia crassipes) Against Fish Pathogens: A Comprehensive Review of Aquaculture Applications
The rapid expansion of aquaculture has been accompanied by an increasing prevalence of infectious diseases caused by bacterial and fungal pathogens, which continue to constrain global fish production. Conventional disease management strategies rely heavily on antibiotics and synthetic chemotherapeutics; however, the emergence of antimicrobial resistance (AMR), environmental contamination, and regulatory restrictions on antibiotic use have stimulated interest in sustainable, plant-based alternatives. Among the aquatic plants investigated, water hyacinth (Eichhornia crassipes), an invasive aquatic macrophyte, has gained considerable scientific attention owing to its rich phytochemical composition and diverse biological activities. The plant contains an array of secondary metabolites, including phenolic compounds, flavonoids, alkaloids, tannins, saponins, and terpenoids, many of which exhibit documented antimicrobial properties. This review critically examines the published literature on the antibacterial and antifungal activities of E. crassipes against microorganisms relevant to aquaculture, with particular emphasis on fish-pathogenic species. The review addresses the phytochemical profile of water hyacinth, extraction methodologies, mechanisms underlying antimicrobial activity, and evidence from both in vitro and in vivo investigations. Furthermore, the potential application of water hyacinth-derived bioactive compounds as eco-friendly alternatives for disease management in cultured fish species is evaluated. Although existing findings indicate promising antimicrobial potential, significant knowledge gaps persist with respect to active compound identification, standardization of extraction procedures, toxicity profiling, and large-scale field validation. Future research integrating phytochemical characterization, molecular approaches, and aquaculture-based challenge studies is anticipated to facilitate the development of E. crassipes-derived therapeutics for sustainable fish health management.
Copyright (c) 2026 Snehan SenthilKumar, Augastin Karunakaran https://creativecommons.org/licenses/by-nc-nd/4.0
Chronopharmacology of Proton Pump Inhibitors in Irregular Meal Timing:Emerging Implications of Breakfast Skipping in Gastroesophageal RefluxDisease (GERD)
Gastroesophageal reflux disease (GERD) is a highly prevalent gastrointestinal disorder associated with substantial impairment in quality of life and increasing healthcare burden worldwide. Proton pump inhibitors (PPIs) remain the cornerstone of GERD pharmacotherapy; howev er, a considerable proportion of patients continue to experience persistent reflux symptoms despite standard treatment. Emerging evidence suggests that irregular meal timing, particularly breakfast skipping, may contribute to both GER D pathogenesis and sub optimal therapeutic response to PPIs. This review examines the chronopharmacological relationship between proton pump inhibitor efficacy, circadian regulation of gastric acid secretion, and disrupted meal timing patterns. Circadian rhythms regulate multipl e gastrointestinal functions, including gastric acid secretion, lower esophageal sphincter tone, gastric motility, and mucosal defense mechanisms, all of which influence reflux pathophysiology. PPIs exhibit meal dependent pharmacodynamics, requiring admini stration prior to food induced proton pump activation for optimal acid suppression. Breakfast omission disrupts this synchronization, potentially impairing proton pump inhibition, reducing intragastric pH control, and increasing the risk of n octurnal acid breakthrough and refractory GERD symptoms. Additionally, prolonged fasting and circadian misalignment may exacerbate reflux through mechanisms involving transient lower esophageal sphincter relaxations, delayed gastric emptying, autonomic dysregulation, neuroimmune signaling, and gut brain axis dysfunction. This review further discusses chronotherapeutic strategies, including individualized PPI dosing schedules, split dose therapy, chrono nutrition approaches, and the emerging role of potassium competitive acid blockers in patients with irregular meal timing. Despite growing epidemiological and mechanistic evidence, significant research gaps remain regarding the direct impact of breakfast skipping on PPI pharmacodynamics and GERD outcomes. Future chronopharm acological and precision medicine based investigations may facilitate more individualized and effective GERD management strategies.
Copyright (c) 2024 Vasanth Albert Rayappan, Alwin Simon M https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Genetic Testing in Predicting Response to Heparin and HeparinInduced Thrombocytopenia
Heparin remains one of the most widely used antic oagulants for the prevention and treatment of thromboembolic disorders; however, significant interindividual variability in therapeutic response and the risk of heparin induced thrombocytopenia (HIT) continue to pose major clinical challenges. HIT is a ser ious immune mediated adverse drug reaction characterized by thrombocytopenia and paradoxical thrombosis, often resulting in substantial morbidity and mortality if not identified promptly. Recent advances in pharmacogenomics and molecular diagnostics have h ighlighted the potential role of genetic testing in predicting heparin responsiveness and susceptibility to HIT. This review comprehensively examines the current evidence regarding genetic determi nants influencing heparin pharmacodynamics, pharmacokinetics , and immune mediated adverse reactions. Particular emphasis is placed on polymorphisms in genes such as FCGR2A, CYP2C9, VKORC1, HLA DR, HLA DQ, TDAG8, and PF4, which have been associated with altered anticoagulant response, platelet activation, and thromb otic risk. The review also discusses the molecular mechanisms underlying HIT, including PF4 heparin complex formation, antibody mediated platelet activation, and thrombin generation. Furthermore, contemporary genetic testing approaches, including genome wi de association studies (GWAS), candidate gene analysis, and next generation sequencing (NGS), are evaluated for their clinical applicability in risk stratification and individualized therapy . The integration of genetic profiling into heparin therapy may fa cilitate personalized anticoagulation strategies, improve patient safety, reduce adverse outcomes, and support precision medicine approaches in thrombosis management. Despite promising advancements, challenges related to clinical validation, cost effective ness, and implementation in routine healthcare settings remain. Future large scale studies and standardized testing algorithms are essential to establish the clinical utility of pharmacogenomic guided heparin therapy and HIT prevention.
Copyright (c) 2026 Nithesh Kumar Haridoss, Krishna Ravi https://creativecommons.org/licenses/by-nc-nd/4.0
The Evolving Role of Biologics and Biosimilars in Future Treatment Strategies
Biologics have transformed modern medicine through highly targeted therapies derived from living systems, including monoclonal antibodies, recombinant proteins, vaccines, and advanced cell and gene therapies. Their molecular specificity has significantly improved outcomes in oncology, autoimmune diseases, endocrinology, haematology, and ophthalmology, enabling disease modification and, in some cases, durable remission or cure. However, biologics are associated with substantial manufacturing complexity, immunogenicity concerns, stringent storage requirements, and high treatment costs, which limit accessibility worldwide. Biosimilars have emerged as a cost-effective alternative following patent expiry of reference biologics. Although not identical to originator products, biosimilars demonstrate no clinically meaningful differences in safety, efficacy, or immunogenicity through a rigorous totality-of-evidence regulatory framework. Regulatory pathways established by the FDA, EMA, and WHO have facilitated the increasing approval and global adoption of biosimilars, resulting in substantial healthcare savings and expanded patient access. Evidence from clinical trials and real-world studies confirms comparable therapeutic performance between biosimilars and reference biologics across multiple therapeutic areas. Despite these advances, challenges remain regarding physician and patient acceptance, interchangeability policies, pharmacovigilance, and regulatory harmonisation. Future developments in personalised medicine, therapeutic drug monitoring, next generation biologics such as bispecific antibodies and antibody-drug conjugates, CAR-T therapies, mRNA therapeutics, and artificial intelligence-assisted drug development are expected to further reshape biologic pharmacotherapy. Pharmacists play a central role in formulary management, patient counselling, biosimilar education, and adverse-event monitoring, supporting the safe and effective integration of biologics and biosimilars into clinical practice. Overall, biologics and biosimilars represent a cornerstone of precision medicine and hold significant promise for improving global healthcare outcomes sustainably and equitably.
Copyright (c) 2026 PaulPraveenKumar DeepakJayakumar, Prathish Murugan, Monisha Thangadurai, Vasanth Albert Rayappan https://creativecommons.org/licenses/by-nc-nd/4.0
Personalized metformin treatment in PCOS: Integrating Artificial intelligenceand Biomarkers
Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder associated with reproductive dysfunction, insulin resistance, metabolic syndrome, and increased long term cardiovascular risk. Metformin remains a cornerstone therapy in PCOS management because of its beneficial effects on insulin sensitivity, ovu lation, menstrual regularity, and metabolic parameters. However, substantial inter individual variability in therapeutic response limits its effectiveness, highlighting the need for precision medicine approaches. This narrative review synthesizes current e vidence regarding biomarkers and artificial intelligence (AI) based strategies for personalizing metformin therapy in PCOS. Key metabolic biomarkers such as HOMA IR, fasting insulin, and HbA1c, alongside hormonal markers including anti Müllerian hormone (A MH), testosterone, luteinizing hormone/follicle stimulating hormone ratio, and sex hormone binding globulin, demonstrate potential in predicting treatment response. Inflammatory biomarkers and emerging molecular markers, particularly microRNAs and pharmaco genomic variants, may further refine patient stratification. The review also evaluates the growing role of AI and machine learning in PCOS diagnosis, risk stratification, and treatment prediction. Machine learning models integrating clinical, biochemical, genomic, and lifestyle data could identify likely responders to metformin before treatment initiation, thereby reducing empirical prescribing and adverse effects. A conceptual AI assisted clinical decision support framework is proposed to guide future tran slational research and clinical implementation. Despite promising advances, challenges related to dataset quality, model interpretability, algorithm bias, and external validation remain signi ficant barriers. Future progress will require multi center collab orations, standardized phenotyping, explainable AI models, and integration of multi omics and digital health technologies to enable truly personalized metformin therapy in PCOS.
Copyright (c) 2025 Jayalakshmi Veeramuthu, kavibharathi Murugan, Sowmiya Jothivel, Vasanth Albert Rayappan https://creativecommons.org/licenses/by-nc-nd/4.0
Emerging Pharmacological Therapies for Paediatric Migraine: From Conventional Treatments to CGRP-Targeted Therapie
Paediatric migraine is a prevalent and disabling neurovascular disorder that substantially impairs academic performance, psychosocial development, and quality of life in children and adolescents. Despite its significant global burden, pharmacological management remains limited by sparse paediatric-specific evidence, high placebo response rates in clinical trials, and reliance on extrapolated adult data. Conventional acute therapies, including non-steroidal anti-inflammatory drugs and triptans, remain the cornerstone of symptomatic management, whereas preventive agents such as topiramate, amitriptyline, propranolol, and flunarizine demonstrate variable efficacy and are frequently constrained by tolerability concerns. The landmark Childhood and Adolescent Migraine Prevention (CHAMP) trial further challenged the effectiveness of traditional preventive therapies by demonstrating no superiority of amitriptyline or topiramate over placebo. Recent advances in migraine neurobiology have identified calcitonin gene-related peptide (CGRP) as a pivotal mediator in trigeminovascular activation and migraine pathophysiology, leading to the development of mechanism-based CGRP-targeted therapies. Anti-CGRP monoclonal antibodies, including erenumab, fremanezumab, galcanezumab, and eptinezumab, together with small-molecule CGRP receptor antagonists (gepants), represent a transformative therapeutic paradigm with improved specificity and favourable tolerability profiles. Emerging paediatric trials such as REBUILD, SPACE, and HEADWAY have provided encouraging preliminary evidence regarding efficacy, pharmacokinetics, and safety in adolescents and children, although long-term developmental safety data remain limited. This review critically examines current pharmacological strategies for paediatric migraine, comparing conventional therapies with emerging CGRP-targeted agents in terms of mechanisms, efficacy, safety, and clinical applicability. Particular emphasis is placed on developmental neurobiology, paediatric pharmacokinetic considerations, methodological limitations of paediatric migraine trials, and future directions in precision-based headache therapeutics. CGRP-targeted therapies hold substantial promise for addressing the unmet therapeutic needs of paediatric migraine; however, rigorous long-term paediatric studies and structured pharmacovigilance remain essential before widespread clinical integration.
Copyright (c) 2026 Gopiarasan Kolamuthu, Harini Madhanmohan, Nithesh Kumar Haridoss https://creativecommons.org/licenses/by-nc-nd/4.0
Resistance Mechanisms to Hormonal Therapy in Endometrial Cancer: AComprehensive Review
Background: Endometrial cancer (EC) is the most common gynaecological malignancy in developed countries, with its incidence rising globally in parallel with obesity and metabolic syndrome. Hormonal therapy, principally progestins and selective oestrogen receptor modulators, represents an essential, fertility-sparing treatment strategy in early-stage, low-grade disease and an alternative systemic option in advanced or recurrent settings. However, a substantial proportion of patients exhibit primary or acquired resistance to hormonal agents, resulting in treatment failure and disease progression. Objectives: This review systematically evaluates the molecular and cellular mechanisms underpinning resistance to hormonal therapy in endometrial cancer, with particular emphasis on receptor-level alterations, intracellular signalling dysregulation, epigenetic modifications, the tumour microenvironment, and emerging biomarkers of resistance. Methods: A comprehensive search of PubMed, Scopus, and Web of Science databases was conducted for original research articles, systematic reviews, and clinical trials published from 2015 to 2025. Search terms included 'endometrial cancer', 'hormonal therapy resistance', 'progestin resistance', 'progesterone receptor', 'PI3K/AKT/mTOR', 'PTEN', 'microsatellite instability', and related terms. Results: Resistance to hormonal therapy in endometrial cancer is multifactorial. Key mechanisms include loss or downregulation of progesterone receptor (PR) and oestrogen receptor (ER) expression, PTEN loss and PI3K/AKT/mTOR pathway hyperactivation, KRAS and CTNNB1 mutations, epigenetic silencing of hormone receptors, altered tumour microenvironment, and upregulation of drug efflux transporters. Emerging evidence implicates mismatch repair deficiency, POLE mutations, and HER2 amplification as modulators of both hormonal responsiveness and therapeutic targetability. Conclusion: A mechanistic understanding of hormonal therapy resistance is critical for optimising patient selection, developing combination strategies, and integrating novel targeted agents and immunotherapy into management algorithms for endometrial cancer. Prospective biomarker-driven clinical trials are urgently needed.
Copyright (c) 2026 Rizwana Sujavudheen, Priyadharshini Dhanusu, Priyavarshini Chinnapparaj, Nithesh Kumar Haridoss https://creativecommons.org/licenses/by-nc-nd/4.0
Deep Learning Approaches for EEGBased Seizure Prediction in PediatricEpilepsy: Current Advances, Challenges, and Future Directions
Pediatric epilepsy is one of the most prevalent neurological disorders in children and is associated with significant cognitive, developmental, and psychosocial consequences. The unpredictable nature of seizures poses substantial challenges for patients, caregivers, and clinicians, emphasizing the need for accurate seizure prediction systems. Electroencephalography (EEG) remains the gold standard tool for seizure monitoring due to its high temporal resolution and ability to capture epileptiform activity. In recent years, deep learning approaches have demonstrated considerable potential in improving EEG driven seizure prediction by automatically extracting complex spatiotemporal patterns from neural signals. This review summarizes current advances in deep learning-based seizure prediction in pediatric epilepsy, focusing on convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, hybrid CNN-LSTM architectures, and transformer-based models. The review also discusses pediatric specific EEG characteristics, signal pre-processing methods, feature extraction techniques, and benchmark datasets commonly used for model evaluation. Although hybrid and transformer-based models have achieved promising predictive accuracies, several challenges continue to hinder clinical translation, including limited pediatric specific EEG datasets, age dependent EEG variability, poor cross patient generalizability, black box model interpretability, wearable device limitations, and ethical concerns regarding pediatric data privacy. Emerging research directions such as explainable artificial intelligence, multimodal biomarker integration, federated learning, wearable EEG technologies, and edge AI systems are also highlighted. Overall, deep learning driven seizure prediction holds substantial promise for personalized pediatric epilepsy management and may significantly improve long term neurological outcomes through early intervention and real time monitoring.
Copyright (c) 2025 Nithesh Kumar Haridoss , Vasanth Albert Rayappan https://creativecommons.org/licenses/by-nc-nd/4.0
Neuroprotective Potential of Medicinal Plants in Alzheimer's Disease: CurrentPerspectives and Therapeutic Advances
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder worldwide, accounting for 60 70% of all dementia cases and affe cting over 55 million individuals globally. Current pharmacological therapies, including acetylcholinesterase (AChE) inhibitors and NMDA receptor antagonists, provide only symptomatic relief and are associated with significant adverse effects , underscoring the urgent need for alternative therapeutic strategies. Medicinal plants, with their diverse phytochemical repertoire, have emerged as promising sources of neuroprotective agents capable of addressing the multifactorial pathogenesis of AD. This revi ew com prehensively evaluates the neuroprotective potential of key medicinal plants including Bacopa monnieri, Curcuma longa, Ginkgo biloba, Withania somnifera, and Centella asiatica, among others. We discuss the molecular mechanisms by which their bioactive cons tituents, encompassing flavonoids, alkaloids, terpenoids, and polyphenols, modulate amyloid beta aggregation, tau hyperphosphorylation, oxidative stress, neuroinflammation, and cholinergic dysfunction. Evidence from preclinical and clinica l studies is crit ically appraised, and emerging nanotechnology based drug delivery approaches to enhance phytochemical bioavailability are explored. The review highlights multi target therapeutic potential of plant derived compounds as a foundation for future integrative a nd evidence based pharmac otherapy in Alzheimer's disease
Copyright (c) 2026 Vasanthapriyan S, Ragulgandhi B https://creativecommons.org/licenses/by-nc-nd/4.0
Comparative Evaluation of Marketed Paracetamol Tablet Brands
Background: The therapeutic reliability of immediate-release solid dosage forms is critically dependent on both their physicochemical quality attributes and the kinetics of in-vitro drug release under physiologically relevant conditions. Paracetamol (acetaminophen) remains among the most widely dispensed analgesics and antipyretics globally, yet inter-brand variability in formulation composition and manufacturing processes may influence dissolution behaviour and, consequently, clinical performance. Objective: This study aimed to conduct a systematic comparative evaluation of three commercially available Paracetamol 500 mg immediate-release tablet brands (Brand A, B, and C) procured from the Indian pharmaceutical market, assessing both compendial quality parameters and multimedia in-vitro dissolution profiles across multiple simulated gastrointestinal pH environments. Methods: Physical quality evaluation encompassed weight variation, tablet thickness, hardness, friability, and disintegration time, conducted in accordance with Indian Pharmacopoeia (IP) guidelines. Dissolution testing was performed using IP Apparatus II (Paddle) at 37 ± 0.5°C and 50 rpm in four dissolution media, Purified Water, 0.1N HCl, pH 4.5 Acetate Buffer, and pH 5.8 Phosphate Buffer with spectrophotometric quantification at 247 nm. Results: All three brands complied with IP weight variation limits (± 5%). Inter-brand differences were observed in hardness (7.20–11.40 kg/cm²), friability (0.13–0.85%), and disintegration time (40 seconds to 3 minutes 06 seconds). In all four-dissolution media, all brands released ≥ 80% of the labelled drug content within 30 minutes, fulfilling the IP dissolution criterion. Brand C, characterized by the highest friability and shortest disintegration time, consistently exhibited the most rapid dissolution profile. Brand B demonstrated the most uniform release pattern, while Brand A achieved robust complete dissolution with the highest structural integrity. Conclusion: The study establishes a demonstrable correlation between physical formulation parameters, particularly friability and disintegration behaviour and in-vitro dissolution kinetics. Multimedia testing confirmed that the dissolution profiles of all three brands are largely pH-independent, attributable to paracetamol's inherently high aqueous solubility. All evaluated brands satisfy IP compendial standards and may be considered pharmaceutically equivalent and therapeutically interchangeable.
Copyright (c) 2026 Ganesan Subramaniyan, Senthil Kumar M, Mariya Rextan R, Dhivagar S, Karpagavalli P, Boomika S, Thilak Kumar K, Maha Priyadarshini R, Nisha A, Nethaji R B, Karthiga G https://creativecommons.org/licenses/by-nc-nd/4.0
Integrative Machine Learning Approaches for Predicting Metformin Responsein Type 2 Diabetes: A Multi Omics Perspective
Background: Type 2 Diabetes Mellitus is a heterogeneous metabolic disorder characterized by variable therapeutic responses. Metformin remains the first line therapy; however, significant interindividual variability in glycemic r esponse limits its effectiveness. Objective: To review and synthesize current evidence on integrative machine learning approaches that combine multi omics and clinical data to predict metformin response in individuals with Type 2 Diabetes. Methods: A compr ehensive narrative review was conducted, focusing on studies integrating pharmacogenomic, metabolomic, and clinical datasets using machine learning techniques such as Random Forest, Support Vector Machines, and neural networks. Data integration strategies including early, intermediate, and late fusion were examined. Results: Individual predictors, including genetic variants (e.g., SLC22A1, ATM), clinical factors (age, BMI, baseline HbA1c), and metabolomic signatures (amino acids, lipids, gut derived metabol ites), explain only a fraction of variability in metformin response. Integrative machine learning models demonstrate improved predictive performance by capturi ng nonlinear interactions across biological layers. However, challenges such as data heterogeneit y, small sample sizes, lack of standardization, and limited external validation persist. Conclusion: Multi omics integration using machine learning offers a promising pathway toward precision medicine in Type 2 Diabetes. Nevertheless, methodological limita tions, interpretability issues, and translational barriers must be addressed before clinical implementation
Copyright (c) 2026 K. Chandramohan, R. Nepolean, V. Balaji, D. Anbarasu, N. Jayaram https://creativecommons.org/licenses/by-nc-nd/4.0
Development and Validation of a UHPLC Method for the Simultaneous Estimation of Hydrochlorothiazide and Amlodipine in Solid Dosage Forms
Background: Hypertension, a leading global cardiovascular risk factor, is commonly managed with combination pharmacotherapy. Hydrochlorothiazide (HCT), a thiazide diuretic, and Amlodipine (AML), a calcium channel blocker, are frequently co-prescribed in fixed-dose tablet formulations to achieve optimal blood pressure control. Despite their widespread co-administration, a validated Ultra-High-Performance Liquid Chromatography (UHPLC) method for the simultaneous quantification of both drugs in solid dosage forms was not available in the published literature at the time of this investigation. Methodology: A UHPLC method was developed and validated on an Agilent system using a C8 column (4.6 mm × 50 mm, 3 µm) operated under isocratic conditions. The mobile phase consisted of 0.02 M potassium dihydrogen orthophosphate buffer (pH 3.0) and acetonitrile (60:40, v/v) delivered at 0.5 mL/min. Detection was performed at 230 nm with an injection volume of 2 µL. Validation was executed in accordance with ICH Q2(R1) guidelines, encompassing system suitability, specificity, linearity, precision, accuracy, and robustness. Results: Hydrochlorothiazide and Amlodipine were resolved at retention times of 1.810 min and 2.911 min, respectively, within a 5-minute run. Linearity was established over 50–150% of the nominal concentration; correlation coefficients were R² = 1.0000 (HCT) and R² = 0.9993 (AML). Assay recovery values were 100.33% (HCT) and 100.07% (AML). Repeatability %RSD values were 0.16% and 0.07%, respectively. Mean accuracy recoveries ranged from 100.60–101.28% (HCT) and 99.57–100.97% (AML). All robustness parameters remained within acceptance criteria under deliberate variations in flow rate and detection wavelength. Conclusion: The proposed UHPLC method is rapid, precise, accurate, and specific for the simultaneous estimation of hydrochlorothiazide and amlodipine. It satisfies ICH validation requirements and is suitable for routine quality control analysis in pharmaceutical manufacturing settings.
Copyright (c) 2026 Boopathyraja R, Ezhilkumar E, Krishna S, Nehamagimai Nisha A, Priyadharshini R, Sivaraj A, Thrisha S, Vinitha R, Ganesan S, Medapati Vijaya Vara Prasad, Kathiravan Mani https://creativecommons.org/licenses/by-nc-nd/4.0
Therapeutic Potential of Benzimidazole Derivatives:AComprehensive Review of Biological Activities
Background: Benzimidazole is a privileged heterocyclic scaffold widely recognized for its structural similarity to purines and its extensive role in medicinal chemistry. Over the decades, benzimidazole derivatives have demonstrated diverse pharmacological activities, making them valuable candidates in drug discovery and development. Objective: This review aims to provide a comprehensive overview of the chemistry, synthesis, mechanism of action, and broad spectrum of biological activities of benzimidazole derivatives, with particular emphasis on their therapeutic potential and recent advancements in green synthetic approaches. Methods: A comprehensive review of published literature was conducted focusing on synthetic methodologies, structure–activity relationships (SAR), and pharmacological evaluations of benzimidazole derivatives. Both classical and modern catalytic approaches, including environmentally sustainable synthesis methods, were analyzed alongside reported biological assays. Results: Benzimidazole derivatives exhibit a wide range of biological activities, including antimicrobial, anticancer, antioxidant, antihypertensive, antidiabetic, and analgesic effects. Their mechanism of action primarily involves interaction with β-tubulin, inhibition of microtubule formation, and disruption of cellular metabolism. Advances in synthesis, particularly green chemistry techniques and catalyst-driven methods, have improved yield, selectivity, and environmental compatibility. Structure–activity relationship studies highlight that substitution at specific positions of the benzimidazole nucleus significantly enhances pharmacological efficacy. Conclusion: Benzimidazole remains a highly versatile and promising scaffold in medicinal chemistry due to its broad-spectrum biological activities and modifiable structure. Continued research focusing on targeted drug design, sustainable synthesis, and optimization of pharmacokinetic properties is essential to fully exploit its therapeutic potential in treating complex diseases.
Copyright (c) 2026 Shriram Govind Kumbhar, Shubhada Vilas Hatakar, SwapnagandhaSatappa Patil, Siddhesh Sadashiv Karade, Kousalya A. Patil, Shobhraj B. Malavi https://creativecommons.org/licenses/by-nc-nd/4.0
Blockchain and Artificial Intelligence in the Pharmaceutical Industry: Enhancing Drug Supply Chain Security and Healthcare Applications
Background: The pharmaceutical industry faces major challenges related to counterfeit medicines, lack of supply chain transparency, inefficient data management, and fragmented healthcare information systems. Counterfeit drugs pose serious risks to patient safety and compromise the integrity of pharmaceutical distribution networks. Emerging digital technologies such as blockchain and artificial intelligence (AI) have gained increasing attention as potential solutions for improving security, traceability, and transparency in pharmaceutical and healthcare systems. Objective: This review aims to examine the role of blockchain technology and its integration with artificial intelligence in strengthening pharmaceutical supply chain security and enhancing healthcare data management. Methods: A literature review was conducted using peer-reviewed publications from 2017 to September 2023. The Scopus database was primarily used to identify relevant studies addressing blockchain applications in pharmaceutical supply chains, healthcare systems, and AI-driven technologies. A total of 353 publications were initially identified, and approximately 121 relevant articles were selected for detailed analysis. Results: The review indicates that blockchain technology provides a decentralized and immutable framework for recording and verifying transactions across pharmaceutical supply chains. Blockchain-based systems enable improved drug serialization, product authentication, and real-time traceability, which can help prevent counterfeit medicines from entering the market. In healthcare, blockchain facilitates secure management of electronic health records, supports clinical trial transparency, and enables reliable patient monitoring. The integration of blockchain with artificial intelligence and Internet of Things (IoT) technologies further enhances data analysis, predictive monitoring, and healthcare decision-making. Conclusion: Blockchain technology has significant potential to improve transparency, security, and efficiency in pharmaceutical supply chains and healthcare systems. Although challenges such as scalability, regulatory issues, and system interoperability remain, continued technological development and collaborative efforts may enable broader adoption of blockchain-enabled healthcare ecosystems.
Copyright (c) 2026 Ramanan M, Rukmangathan Palani, Sangavi G, Senthilnathan D N, Praveena S, Kalaikumar S, Jeevitha Moorthy https://creativecommons.org/licenses/by-nc-nd/4.0
Insilico ADMET and molecular docking study of novel antihypertensivederivatives designed by bioisosteric replacement of the aminoquinazoline ringin prazosin
Considering the global burden of hypertension, this study aims to design and evaluate novel Prazosin analogues with enhanced pharmacokinetic properties and reduced toxicity using a bioisosteric approach. This study will help to find the prominent group for antihypertensive drug development. A bioisosteric approach was employed to generate novel Prazosin analogues using the MolOpt program. The aminoquinazoline moiety of Prazosin was systematically replaced with bioisosteric groups, and the various pharmacoki netics (absorption, distribution, metabolism, excretion, and toxicity) parameters of the newly developed analogs were calculated. Molecular docking studies were performed to assess the binding affinity of the newly designed analogues, and the top three der ivatives with superior docking scores were identified. The study identified several compounds as promising analogues due to their reduced toxicity (hERG, H HHT, DILI < 0.3), favorable drug likeness QED values (≤ 0.67), and molecular docking score compared to prazosin. Notably, analogues 038, 158, and 190. This study successfully identified novel antihypertensive derivatives with improved ADMET properties, enhanced drug likeness, and favorable molecular docking profiles. The findings provide valuable insight s for the development of next generation antihypertensive agents with optimized pharmacological characteristics.
Copyright (c) 2026 Sunil Sahu, Pankaj Minj, Dhansay Dewangan, Swarnlata Saraf, Rakesh Tirkey https://creativecommons.org/licenses/by-nc-nd/4.0
Role of Pirfenidone in Autoimmune Disorders and ImmunoOncology: AComprehensive Review
Background: Pirfenidone, originally developed as an antifibrotic agent for idiopathic pulmonary fibrosis (IPF), has emerged as a pro mising therapeutic candidate with pleiotropic immunomodulatory properties that extend beyond its established pulmonary indication. Objective: This review aims to systematically examine the detailed molecular mechanisms underlying pirfenidone's antifibrotic , anti inflammatory, and immunomodulatory activities across key signaling pathways including TGF β/SMAD, NF κB, JAK/STAT, and PI3K/Akt; critically evaluate preclinical and clinical evidence for pirfenidone in autoimmune diseases particularly systemic scler osis, rheumatoid arthritis, lupus nephritis, and inflammatory bowel disease; assess its emerging role in immuno oncology through modulation of the tumor microenvironment; and contextualize pirfenidone within the broader landscape of antifibrotic and immuno modulatory therapies through comparative analysis with nintedanib, mycophenolate mofetil, methotrexate, and targeted biologics. Methods: A comprehensive search of PubMed, ClinicalTrials.gov, Embase, and major conference proceedings (through 2025) was condu cted. Preclinical studies, randomized controlled trials, observational studies, and phase I III clinical trial reports were included and critically appraised. Results: Pirfenidone exerts antifibrotic effects primarily through inhibition of TGF β1 induced S MAD2/3 phosphorylation and suppression of connective tissue growth factor (CTGF) expression, while anti inflammatory properties are mediated through NF κB pathway blockade, modulation of the JAK2/STAT3 axis, and suppression of TNF α, IL 1β, IL 6, and IL 13 . In autoimmune diseases, the LOTUSS Phase 2 trial confirmed tolerability in systemic sclerosis associated ILD, with ongoing SLS III (NCT03221257) examining combination with mycophenolate mofetil. In rheumatoid arthritis, pirfenidone inhibits synovial fibr oblast activation via JAK2/STAT3 and Akt pathways. In immuno oncology, pirfenidone targets cancer associated fibroblasts (CAFs), reduces desmoplastic stroma, enhances CD8+ T cell tumor infiltration, and demonstrates synergy with immun e checkpoint inhibitor s in preclinical pancreatic, colorectal, and non small cell lung cancer models. Compared to nintedanib currently the only other dual approved antifibrotic pirfenidone offers distinct mechanistic advantages, including direct cytokine pathway modulation and superior CAF inhibitory effects. Conclusion: Pirfenidone represents a compelling drug repositioning candidate with a mechanistic rationale spanning autoimmune fibroinflammatory diseases and immuno oncology. Ongoing and planned clinical trials are expected to define its role within evolving therapeutic algorithms. Integration of predictive biomarkers and rational combination strategies will be critical to realizing its full therapeutic potential.
Copyright (c) 2026 Ch Sandeep Reddy, Repudi Lalitha https://creativecommons.org/licenses/by-nc-nd/4.0
Current Status of Pharmacovigilance in Herbal and Traditional Medicines: A Review.
Pharmacovigilance is the study of the safety of pharmaceutical medicines to monitor and detect adverse drug reactions, which may be unrecognized during clinical trials. Traditional medicines often use herbal components, and some of them can cause severe adverse effects. Yet the safety of herbal or traditional medicines is unknown, even though they are believed to be safe. This area of pharmacovigilance is still in an immature stage, although there are multiple herb-drug interactions, herb-herb interactions, and certain herbal products are contraindicated in some conditions. The pharmacovigilance of herbal medicines is still in its immature stage,although the World Health Organization (WHO), the US Food and Drug Administration (FDA), and various agencies in different countries have established reporting systems for adverse drug reactions. But most of the cases go unreported. This review presents the status of herbal pharmacovigilance and highlights the importance of implementing pharmacovigilance procedures for polyherbal medications, promoting rational use and appropriate treatment methods.
Drug-Related Side Effects and Adverse Reactions
Copyright (c) 2026 Dr Elizabeth Kuruvilla https://creativecommons.org/licenses/by-nc-nd/4.0
Design and Development of Press Coated Pulsatile Release of KetoprofenTablets
Ketoprofen pulsatile tablets were developed and evaluated in this work utilizing synthetic polymers grades Hydroxy propyl methyl cellulose ( HPMC) E5, HPMCE15, and natural polymer xanthan gum. The angle of repose and compressibility index were determined to be within the acceptable range by pre formulation investigations of core tablet granules, demonstrating excellent flow properties for compression. The core tablet underwent evaluation procedures that examined content homogeneity compliance, w eight fluctuation within standard deviation (SD) ± 2%, hardness, and friability. Evaluations of the coated tablets showed that the weight fluct uation, hardness, and friability all fell within SD ± 2%. In vitro dissolving tests were conducted on formulation s F1 through F9, and at the conclusion of the sixth hour, formulation 8 produced a pulsatile drug release. After the allotted period, the medication was released here at once. The stability study, which was conducted for two months for formulation 8 in acc ordance with International council of Harmonisation ( ICH) requirements, was determined.
Copyright (c) 2025 Srujana Gandrathi, Padamatini Naveen kumar, Chandrasekhara Rao Baru, Sushma Desai, M. Shiroja, Raaga swetha https://creativecommons.org/licenses/by-nc-nd/4.0
Therapeutic Drug Monitoring (TDM): A Necessity in Critical Care and Transplant Settings
Therapeutic drug monitoring (TDM) personalizes dosage by quantifying plasma concentrations to enhance treatment effectiveness and reduce toxicity. In critically sick patients and transplant recipients, pathophysiological alterations, restricted therapeutic indices, and organ support measures frequently result in unexpected pharmacokinetics (PK). This study emphasizes TDM's significance in critical care and transplantation, concentrating on antimicrobials such as vancomycin, β-lactams, antifungals, and immunosuppressants like tacrolimus, cyclosporine, and mycophenolic acid, substantiated by PubMed-cited literature.
Copyright (c) 2025 Rashmi Agrawal https://creativecommons.org/licenses/by-nc-nd/4.0
Bioorthogonal Chemistry in Drug Discovery: Techniques and Applications in Targeted Cancer Therapy
Bioorthogonal chemistry represents a transformative platform in modern biomedical research, enabling chemical reactions to occur within living systems without interfering with native biochemical pathways. These reactions have provided powerful tools for selective drug activation, non-invasive imaging, and precise biomolecular labeling. In oncology, bioorthogonal strategies offer unique opportunities for targeted drug delivery, pretargeted imaging, and the development of antibody–drug conjugates with improved safety profiles. Key reaction classes—including strain-promoted azide–alkyne cycloaddition (SPAAC), inverse electron demand Diels–Alder (IEDDA) ligation, and sulfur fluoride exchange (SuFEx)—have shown distinct advantages in terms of speed, selectivity, and compatibility with physiological environments. This review summarizes the fundamental principles, reaction mechanisms, and recent advances in bioorthogonal chemistry, with a particular emphasis on applications in targeted cancer therapy. Current challenges, such as reagent stability, delivery efficiency, and translational barriers, are critically discussed. Future perspectives highlight integration with nanotechnology, artificial intelligence, and immunotherapy, which may accelerate the clinical translation of bioorthogonal strategies into precision oncology.
Copyright (c) 2026 Peddinti Kalpana, Sridhar Siddiraju, Muvvala Sudhakar https://creativecommons.org/licenses/by-nc-nd/4.0
Application of Artificial Intelligence in drug discovery, designing, clinical trials and repurposing
Drug development, right from discovery, designing, and repurposing, along with various phases to clinical trials, is a complex and time-consuming process that traditionally relies on the experience of labor forces, along with incessant trial-and-error experimentation. The emergence of various artificial intelligence (AI) tools and techniques is redefining the pharmaceutical industry. The integration of AI-driven methodologies into all stages of the drug development pipeline has enhanced the efficiency and effectiveness of the process. With this review, we aim to provide insights into the application of AI at various stages mentioned, with an emphasis on the latest advancements. The role of AI in speeding up the process of drug development while giving distinct and accurate outcomes is highlighted as well. Finally, we addressed the current challenges in employing AI along with future perspectives in order to enhance AI-augmented drug development, ultimately offering significant benefits to patients and society.
Copyright (c) 2025 Rashmi Agrawal, Meghashyama Kulkarni https://creativecommons.org/licenses/by-nc-nd/4.0
Evaluation of hair growth potential of Angustifolia leaves hair gel in rats
Background: Hair loss, or alopecia, significantly affects both physical appearance and psychological well-being, particularly in cases such as androgenetic alopecia and alopecia areata. Current pharmacological treatments like minoxidil and finasteride have limitations, including side effects and decreased long-term efficacy. Objectives: An ethanolic extract of Senna angustifolia (EESA), a traditionally used Ayurvedic plant, was evaluated for its hair growth-promoting potential using in vivo rat models. Methodology: The research began with the successful extraction of phytoconstituents from Senna angustifolia leaves using Soxhlet extraction. The gel was formulated into two concentrations—2.5% and 5% EESA—and compared with a control and standard 2% minoxidil treatment. Hair growth studies were performed on Wistar rats by evaluating both qualitative (initiation and completion of hair growth) and quantitative parameters (hair length, follicle count, and histological observations). Results: Qualitative hair growth analysis indicated that both EESA concentrations accelerated hair growth, with 5% EESA (HG2) showing a significantly faster initiation and completion time (7.01 and 32.4 days, respectively) compared to control (13.8 and 42.6 days) and even slightly outperforming minoxidil (7.07 and 33.0 days). Quantitative analysis supported these findings. By day 30, HG2 achieved the greatest hair length (2.8 mm), marginally higher than minoxidil (2.4 mm) and significantly more than the control (1.2 mm). Histopathological studies corroborated these findings with increased follicle density and size. Conclusion: These results suggest that Senna angustifolia extract exhibits promising hair growth-stimulatory effects and may serve as a natural alternative or complementary treatment for alopecia with minimal irritation potential. Further clinical investigations are warranted to explore its therapeutic application in humans.
Copyright (c) 2025 Manu Bharti, Anjali Bhardwaj, Neha Parveen, Ashwani Gupta https://creativecommons.org/licenses/by-nc-nd/4.0
Analytical Method Development and Validation
The main objective of the pharmaceutical business is to consistently and economically create goods with the requisite features and quality. The process of finding, creating, and assessing pharmaceutical formulations requires the creation of a methodology. The primary goal of this review article is to examine how the medication development and validation process was carried out, from the beginning of the formulation to the end of the commercial batch. Reliability of the results is essential whenever an analytical method is used to generate results for an array of samples related to medicine. In the pharmaceutical sector, good manufacturing practice (GMP) rules and good laboratory practices (GLP) are adhered to by means of defined validation policies, forms of validation, and validation criteria. Validation is crucial to the efficient operation of the pharmaceutical sector. Validation was done everywhere, from the raw material to the final, stable state. The procedure was appropriately designed, and the validation parameters—specificity, accuracy, quantitation, ruggedness, robustness, and system appropriateness testing—are specified in terms of limit of detection (LOD), limit of quantitation (LOQ), robustness, and ruggedness with reference to specific drug examples. Both the methodology and evaluation of stability make use of all the validation parameters.
Copyright (c) 2024 Rutik Nitin Patil; Bhupendra L Deore; Darshan Ganesh gurav https://creativecommons.org/licenses/by-nc-nd/4.0
EVALUATION OF ANXIOLYTIC ACTIVITY OF ETHANOLIC EXTRACT OF Phyllanthus niruri LEAVES IN MICE
Anxiety has become one of the most prevalent and widely experienced mental illnesses, affecting 7-30% of the world’s population. It is characterized as a distressing psychological state of mind, which is represented by internal feeling of uneasiness, stress and agony. Various theories, including psychodynamic, psychoanalytic, and genetic perspectives, have been proposed to explain the etiology of anxiety disorders. Certain drugs used for treatment of anxiety have side effects and limitation such as sedation, central complexity, and habituation and during withdrawal of drug. Researchers are actively exploring natural remedies, especially medicinal plants, to address anxiety disorders and minimize potential side effects associated with conventional drugs. Hence in the present study we investigate the anxiolytic activity of the plant Phyllanthus niruri leaves in mice using various experimental models such as Elevated Plus Maze and Light And Dark Chamber. In the Elevated Plus Maze (EPM) model, parameters measured included the number of entries in open and closed arms, along with the time spent in each. In the Light and Dark Chamber, measurements encompassed the number of crossings between light and dark sides recorded for 10 minutes, along with the time spent in each side. The administration of the different doses of the plant extract produced significant difference in the locomotor activity of the mice.
Copyright (c) 2024 Spandana Savvaser, Rakshitha Poojary, Soubiya Mahnoor Habibullah, Ashoka Shenoy M https://creativecommons.org/licenses/by-nc-nd/4.0
A case of pediatric autoimmune neuropsychiatric disorder associated with streptococcal infection
Pediatric autoimmune neuropsychiatric disease associated with streptococcal infection (PANDAS), is a subtype of acute-onset obsessive-compulsive disorder (OCD) induced by an immunological reaction to group A streptococcal infection. These diseases may be worsen by an autoimmune response brought on by streptococcal infections. One of the recurring diseases linked to PANDAS is recurrent streptococcal tonsillitis. "Strep throat" (acute suppurative tonsillitis) is a tonsil infection typically caused by Group A Beta-Hemolytic Streptococci (GABHS) bacteria, often leading to intense throat pain, fever, and difficulty swallowing for a few days. Health care providers frequently use a rapid strep test to check the tonsils of patients experiencing a sore throat for GABHS, as untreated infections can lead to more severe health issues. Occasionally, strep throat can result in a body rash (known as scarlet fever) and can also lead to more severe health issues such as arthritis in children, rheumatic fever that can cause long-lasting heart problems, and post-streptococcal glomerulonephritis which may result in kidney failure. Here we present a case of 20-year-old male patient with PANDAS, who underwent tonsillectomy. The morbidity associated with this neuropsychiatric condition can be reduced with prompt management.
Copyright (c) 2024 Dr.Reshma R, Dr. Ajnas K https://creativecommons.org/licenses/by-nc-nd/4.0
Alum-based Herbal Handwash: Formulation and Evaluation Study
Hand washing is one of the most important strategies for preventing the spread of surface-borne diseases. A variety of hand washes are currently available on the market, the majority of which are alcohol-based and synthetic. Since synthetic substances can cause various allergic reactions among people, as well as roughness of the skin, society's interest has shifted towards the use of herbal hand washes. However, in addition to the herbal extracts, we investigated alum as one of the most ancient and effective antimicrobial ingredients in hand wash formulations. In this study, F-1 to F-5 formulation batches of hand washes were prepared using a trial and error method by varying the quantity of ingredients used. In these formulations, hydro-alcoholic extracts of lemon peels and reetha, as well as lemon grass oil as a volatile oil and alum as a mineral, were used as the main constituents, which were analysed by phytochemical screening. These formulations were then evaluated using a variety of methods, such as pH, foam height, foam retention, skin irritation, stability study, and an antimicrobial assay. According to our findings, the alum-based F-3 formulation performed significantly better than the other formulations. With the success of this study, we can conclude that, in the future, as herbal drug technology advances, various hygienic and life-saving products will firmly hold their place in human life.
Copyright (c) 2024 Mohit J. Umarkar, Pawan V. Jibhkate, Payal G. Thakare, Nilesh B. Banarase, Koshish B. Gabhane, Vikrant L. Salode https://creativecommons.org/licenses/by-nc-nd/4.0
Decoding Leptin: Unraveling the Role of Leptin Signaling in the BattleagainstObesity
Obesity represents a major global health crisis, linked to a spectrum of metabolic disorders, including diabetes, cardiovascular diseases, and hypertension. Leptin, a hormone predominantly produced by adipose tissue, plays a critical role in regulating energy balance, appetite, and metabolism. Historically, leptin was believed to be a cornerstone in the management of obesity due to its ability to suppress appetite. However, the effectiveness of leptin therapy has been limited by the phenomenon of leptin resistance in obese individuals. This review, titled "Decoding Leptin: Unraveling the Role of Leptin Signaling in the Battle Against Obesity," aims to delve into the molecular intricacies of leptin signaling pathways and their implications in obesity management. We explore the mechanisms underlying leptin resistance, the impact of leptin on neuroendocrine pathways, and the potential for resetting leptin sensitivity as a therapeutic strategy. Additionally, we discuss recent advances in therapeutic approaches aiming to enhance leptin sensitivity or mimic its effects, including novel pharmacological agents and lifestyle modifications that influence leptin signaling. By providing a comprehensive overview of current research and emerging therapies, this review seeks to illuminate the path forward in leveraging leptin signaling for more effective obesity interventions.
Copyright (c) 2024 Soumyadip Singha, Soumyadip Nayak, Rahul Bishayee, Pritam Sarkar, Priyanka Ghosh, Udita Dutta, Poulomi Mishra https://creativecommons.org/licenses/by-nc-nd/4.0
QBD Approach and Chemo metric Method Development for the estimation of Metoprolol succinate and Cilnidipine in combined solid dosage form
Background: Development of several pharmaceutical processes including analytical methods by applying Quality by design assists in ensuring the robustness of the method. USFDA and other regulatory agencies have recommended implementation of Quality by design (QbD) a systematic process for pharmaceutical development along with its significance. Objective: Chemo metric assisted UV-VIS spectrophotometric analytical method based on QbD was developed for the estimation of metoprolol succinate (MET) and cilnidipine (CIL) from the combined dosage forms. Method: Nature of spectra focused applicability of absorbance correction and amplitude modulation methods for estimation of both drugs from the formulations; and 50 % alcohol was being the common solvent. For both this method 221 nm and 242 nm was the wavelength for measurement of absorbance of metoprolol and cilnidipine respectively. Effect of input variables on spectrum characteristics were studied for selection of critical parameters and developed method was validated as per ICH Q 2 R1 regulatory guidelines. Result and conclusion: Linearity of the drugs was ascertained over the conc range 1-36 μg/ml (microgram/ml) for MET and 1-16 μg/ml for CIL. The percentage purity of assay in method II was found 103.773 % for MET and 96.825 % for CIL; and the accuracy study data of method I were varied 2.04859 for MET and 1.26321 for CIL. Precision study was shown acceptable data as % RSD in method I data varied 0.58894 for MET and 1.15116 for CIL. The developed method is rigid, robust and efficient for the estimation of MET and CIL from the composition of dosage form.
Copyright (c) 2024 G. K. Dyade, R. B. Jadhav, Sanket Repal, Shital Uparwad, Prashant Suryawanshi, Aashish Taware, Sonali Khapne, Shweta Kokare, Anuse Dnyaneshwar https://creativecommons.org/licenses/by-nc-nd/4.0
A New Path for Drug Delivery by Multiple Unit Pellet System (MUPS)
Innovative delivery system that are helpful in enhancing therapeutic objectives and reducing adverse effects are the focus of pharmaceutical research. The advantages of tablets and pellet-filled capsules are combined into a single dose form by MUPS, one of the more complex and inventive technologies. Continuous drug distribution into the bloodstream is made possible by the breakdown of these pills in the stomach and intestine. The current article examines the potential benefits, desirable pellet characteristics, different pelletization methods, MUPS-influencing factors, drug release mechanisms, and pharmaceutical applications, as well as the challenges associated with compaction and the crucial elements that must be considered for MUPS production to be successful.
Copyright (c) 2025 Harshada Rajendra Bafna; Nitin Rajendra Shirsath, Vaibhavkumar Arun Jagtap https://creativecommons.org/licenses/by-nc-nd/4.0